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17 Hours Help Information |
| Regular Class Program ~ S1, D3, S2
(lecture time flexible and can be selected ➜ morning or afternoon / evening) |
See also : » Other Studies Program| Study Program Name | : | Bachelor of Data Science (S-1) | | Science group | : | | | Concentration / Specialisation | : | ⛤ | | Graduate Title / Mention | : | Bachelor of Data Science | | Title abbreviations according EYD | : | S.Si.D | | Title abbreviations are popular (used public) | : | S.Si.D | | PTS organizers (please click) | : | ⛤ UICI Insan Cita Indonesia University | | Study Period & Study Load (Credits) : | SMA/SMU, SMK graduates, equivalent proceed to
S1 Sains Data | Study Load = 144 - 152 sks | Study Period =
8 semester | D3, Polytechnic graduates, equivalent proceed to
S1 Sains Data | Study Load = 40 - 46 sks
(If not a piece of science additional are given 2 - 21 sks) | Study Period =
3 semester | D2, S1, D1 graduates, transfer proceed to
S1 Sains Data | Study Load = Calculated from remaining credits | Study Period =
Calculated remaining credits |
| | Curriculum / Subjects Courses | : | See below | | Prospectus (Objectives, Competencies, Job Prospects / Career Graduates) | : | See below |
Title/mention above is a title often used (not necessarily used PTS).
Regarding title (for S1, S2, S3) or mention (for diploma) which is used by universities in Indonesia currently has no standard (not standard) again, although the government has made the rules, but most colleges only obey some of the rules the. It can not be blamed, because the development of the science group is very rapid and led to new branches of science which is an integration of several scientific groups, making it difficult for universities to classify these branches of the science group that created the government.
Similarly, by making short title / mention such, people tend to create their own abbreviations that are even more popular than EYD Indonesian rule.
Below given curriculum / course and prospectus (competency, job prospects / career graduates, etc.). For subjects study program of presented here is a slice (and some combination) of a college curriculum, so it is possible some no elective courses at the college, or the slightly different name of his courses.
| Prospectus S1 Data Science |
Data Science is an applied science that specifically studies and analyzes data.
This major prepares its graduates to become experts who can handle data (both structured and unstructured),
solve problems, and make recommendations based on data.Educational Goals:S1 Data Science
The educational goals of the Data Science Undergraduate Study Program are as follows:
1. Provides a deep understanding of basic concepts in data processing and analysis.
2. Apply data science concepts in business and industrial contexts.
3. Study decision making, risk management, predictive modeling, optimization, and product development.
4. Applying ethical principles in the collection, processing, and use of data to ensure that the data
used responsibly and respecting individual privacy.Competence of graduates:S1 Data Science
• Able to master statistical and mathematical concepts and methods in processing and analyzing data for
generate recommendations when the decision-making process.
• Be able to choose tools / methods / software that are as needed in their professional practice to take
decision based on available information.
• Able to integrate data science concepts and practices to support decision-making processes.
• Able to master programming models, programming languages, databases, information retrieval, data visualization, andinteractive web page interface.
Profession and Career GraduatesBachelor Of Data Science
• Data Scientist
• Data Analyst
• Data Science Architect
• Business Analyst
• Ahli Statistik (Statistician)
• Machine Learning Engineer.
* = Specific / General Courses
| Subjects | SKS | | Religion I | 2 | | Pancasila | 2 | | Citizenship | 2 | | Indonesian | 2 | | List and Library | 2 | | Basic Biology | 2 | | Basic Chemistry | 2 | | Introduction to Statistics | 3 | | Introduction to Programming | 2 | | Logic and Critical Thinking | 3 | | Introduction to Scientific Collaboration | 2 | | Communication and Personal Development | 2 | | Basic Physics | 2 | | Math | 3 | | Introduction to Advanced Technology | 2 | | Statistical Method | 4 | | Programming Algorithm I | 3 | | Advanced Math | 3 | | English | 2 | | Nonparametic Statistics | 3 | | Probability | 4 | | | | Subjects | SKS | | Green Technology | 2 | | Data exploration and visualization | 3 | | Operations Research | 3 | | Introduction to Artificial Intelligence | 3 | | Mathematical Statistics | 3 | | Statistical Computing | 3 | | Introduction to Databases | 4 | | Data Mining I | 4 | | Mathematical Method | 3 | | Multivariate | 3 | | Data Mining II | 4 | | Database | 4 | | Stochastic Process | 3 | | Academic Research and Development Expertise | 3 | | Religion II | 2 | | Fieldwork Practice | 2 | | Research Method | 2 | | Data Science Consulting | 3 | | Entrepreneurship | 2 | | Thesis | 4 | |
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